Paula Nurius - US grants

Sexual violence is endemic in our society. Research indicates that up to 80% of women experience some form of sexual aggression, perpetrated primarily by someone they know. One important aspect of rape prevention is women's ability to appraise risky situations and to resist aggression effectively. The present project will apply a cognitive coping and adaptation model within an ecological framework to determine which contextual factors have the greatest impact on a woman's perception of threat; emotional responses; sense of mastery; and ultimately her behavioral response. The underlying premise for this research is that behavioral responding is mediated through preceding cognitive processing of the event. The influence of background factors, such as prior victimization, assertiveness, courtship socialization, and peer norms will also be examined. Ultimately, this knowledge can be employed to develop useful rape prevention and resistance programs.

DESCRIPTION (provided by applicant): The University of Washington School of Social Work (UWSSW) proposes to continue a predoctoral Prevention Research Training Program whose main objective is to increase the cadre of well trained behavioral scientists in the field of mental health to conduct socially significant innovative research aimed at the prevention of mental health problems and disorders in vulnerable populations. The training program includes a multidisciplinary group of faculty, and builds upon a strong research tradition and a highly regarded doctoral program in the School of Social Work. Funds are requested to support 7 predoctoral trainees per year in each of five years of the proposed new funding cycle. The predoctoral training program requires completion of all currently existing requirements for the social welfare doctoral degree. In addition, prevention science trainees will complete a) specialized course content in prevention research, b) additional course work in research methods, c) additional course work in social science theory germane to their prevention focus, d) an integrative seminar spanning each year in the training program, e) hands-on research internship each year on a prevention research project, f) infusion of prevention research with mental health issues into their program of study prospectus, qualifying paper, and dissertation, and g) specialized, individually tailored mentoring and advising to ensure a coherent educational program and finely tuned professional development for prevention research careers. Trainees will be recruited from a national pool of applicants and must have strong academic records, a demonstrated interest in prevention of mental health disorders and problems, and strong potential for research. The training program matches very well priorities set by NIMH for interdisciplinary training, preparation for careers in health promotion and prevention of mental disorders, and redressing mental health disparities. The high level of research activity, number of experienced prevention researchers, and commitment to diversity at the University of Washington and in the School of Social Work provide an excellent environment for training that is responsive to high priority needs in prevention. The success of the program thus far is enhanced by faculty newly added to the UWSSW and Training Program combined with newly funded centers and initiatives which, collectively, position the program extremely well to meet its training objectives in this proposed third cycle of funding.

Increasing diversity in engineering and computer science has been a goal that remains elusive. Despite significant efforts, underrepresented minorities received only 16.1% and women received only 21.9% of engineering degrees in 2018. The reasons for these low numbers are complex and multifaceted and discrimination is an important factor in why students from these groups leave engineering. The goal of this research is to develop a holistic understanding of the impact of discrimination on historically underrepresented engineering students. In this era of big data and readily available technology such as mobile phones and wearables, a comprehensive change in how data about the college student experience are collected and assessed is possible. One can now move from lab to field, connect action to behavior, and collect longitudinal data. This, in turn, makes it possible to understand bias and its impact on engineering education in new ways: By complementing self-reports with passive data collection, big data can be used to create an image of behavior while learning about specific challenges underrepresented minority and female engineering students face.

The project will result in a uniquely powerful longitudinal data set, which captures real-time changes in student experiences and allows study of the impact of discrimination at scale across a variety of contexts. The project will quantify the scope, direction, and longitudinal impact on behavior and link this to long-term outcomes such as GPA and retention. This ability to connect behavior to experience in the field was lacking in past studies of discrimination. Analytic techniques capable of capturing both individual variance and looking at unequal numbers of observations, such as hierarchical linear modeling, are required due to the large sample (N=200/year) and number of variables. The data are collected at a large public university and will be most applicable to similar programs at similar institutions. The research will support policy making and intervention design in engineering programs. The ultimate goal is to diversify the pool of engineering students, which will be of direct benefit to society by increasing representation and the range of perspectives engaged in the engineering and computer science workforce.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.